Our Company

At Teradata, we believe that people thrive when empowered with better information. That’s why we built the most complete cloud analytics and data platform for AI. By delivering harmonized data, trusted AI, and faster innovation, we uplift and empower our customers—and our customers’ customers—to make better, more confident decisions. The world’s top companies across every major industry trust Teradata to improve business performance, enrich customer experiences, and fully integrate data across the enterprise.

Ignite the Future of Language with AI at Teradata!

What You'll Do: Shape the Way the World Understands Data

At Teradata, we're not just managing data; we're unleashing its full potential. Our ClearScape Analytics™ platform and pioneering Enterprise Vector Store are empowering the world's largest enterprises to derive unprecedented value from their most complex data. We're rapidly pushing the boundaries of what's possible with Artificial Intelligence, especially in the exciting realm of autonomous and agentic systems

We’re building intelligent systems that go far beyond automation — they observe, reason, adapt, and drive complex decision-making across large-scale enterprise environments. As a member of our AI engineering team, you’ll play a critical role in designing and deploying advanced AI agents that integrate deeply with business operations, turning data into insight, action, and measurable outcomes.

In this role, you’ll architect foundational components for production-grade AI systems — from agent frameworks and LLM pipelines to observability and evaluation layers that ensure reliability, accountability, and performance. You’ll be responsible not just for building models, but for making them measurable, debuggable, and trustworthy in real-world, high-stakes deployments.

You’ll work alongside a high-caliber team of AI researchers, engineers, and data scientists tackling some of the hardest problems in AI and enterprise software — from scalable multi-agent coordination and fine-tuned LLM applications, to real-time monitoring, drift detection, and closed-loop retraining systems.

If you're passionate about building intelligent systems that are not only powerful but observable, resilient, and production-ready, this role offers the opportunity to shape the future of enterprise AI from the ground up.

Who You'll Work With: Join Forces with the Best

Imagine collaborating daily with some of the brightest minds in the company – individuals who champion diversity, equity, and inclusion as fundamental to our success. You'll be part of a cohesive force, laser-focused on delivering high-quality, critical, and highly visible AI/ML functionality within the Teradata Vantage platform. Your insights will directly shape the future of our intelligent data solutions.

You'll report directly to the inspiring Sr. Manager, Software Engineering, who will champion your growth and empower your contributions.

What Makes You a Qualified Candidate: Skills in Action

• Design and prototype interfaces for interacting with autonomous agents.
• Implement responsive, accessible, and explainable UI components that visualize AI decisions, uncertainty, and reasoning paths.
• Partner with AI researchers and software engineers to ensure interfaces support emerging agent capabilities.
• Conduct usability testing with humans-in-the-loop scenarios.
• Drive UX best practices around safety, trust calibration, and explainability for intelligent systems.
• Design and prototype intuitive, high-impact interfaces for interacting with autonomous and intelligent agents.
• Experiment with LLM APIs, agentic workflows, and cutting-edge open-source frameworks
• Explore and implement planning systems, vector databases, or memory architectures such as graph-based storage on Teradata
• Champion UX best practices around safety, trust calibration, and explainability for intelligent systems.
• Collaborate with AI researchers and software engineers to ensure interfaces evolve alongside emerging agent capabilities.
• Develop and enhance native notebook experiences that blend code, data, and visualization — enabling seamless interaction with LLMs, agents, and AI workflows
• Embrace DevOps practices, integrating UI development with continuous integration and deployment pipelines for rapid iteration and smooth deployment.
• Implement unit tests for UI components to ensure reliability and maintain high-quality user experiences.
• Strong engineering background (Python/Java/Golang, API integration, backend frameworks)
• Strong system design skills and understanding of distributed systems.
• You’re obsessive about reliability, debuggability, and ensuring AI systems behave deterministically when needed.

What You Bring: Passion and Potential

• A Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field – your academic foundation is key.
• A genuine excitement for AI and large language models (LLMs) is a significant advantage – you'll be working at the cutting edge!
• Experience in UI/UX design and frontend engineering.
• Proficiency in Angular, TypeScript, Figma, and design systems.
• Experience developing native notebook interfaces or extensions (e.g., Jupyter, VS Code Notebooks, or custom notebook UIs) is a strong plus.
• Strong understanding of human-computer interaction (HCI), especially with intelligent systems.
• Experience designing interfaces for complex workflows or ML-powered products is a plus.
• Bonus: Experience with LLM-based tools or agent orchestration (e.g., LangChain, AutoGen).
• You're knowledgeable about open-source tools and technologies and know how to leverage and extend them to build innovative solutions.
• Passion for AI/ML, especially in building smart, agent-driven interfaces that feel human.
• Ownership mindset — you build, deploy, iterate, and scale with a long-term view.
• Unit Testing & Quality: Experience implementing unit tests for UI components to ensure robustness and maintainability.
• DevOps Familiarity: Comfortable with DevOps methodologies, including CI/CD processes to integrate UI development into automated deployment pipelines
• Experience in software development (Python, Go, or Java preferred).
• Familiarity with backend service development, APIs, and distributed systems.
• Interest or experience in LLMs, autonomous agents, or AI tooling.
• Familiarity with containerized environments (Docker, Kubernetes) and CI/CD pipelines.
• Containerization & Orchestration: Strong familiarity with containerized environments using Docker and Kubernetes (K8s) for deploying and managing AI/ML workloads at scale.
• CI/CD Pipelines: Experience in implementing and maintaining continuous integration and continuous deployment (CI/CD) pipelines to streamline model training, testing, and deployment processes in production environments.
• Experience in automating ML workflows using tools like Kubeflow, MLflow, or Argo Workflows is a plus.
• Knowledge of monitoring and scaling ML services on Kubernetes clusters (e.g., using Prometheus, Grafana, or KServe).

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